One of the greatest goals of smart networks is to make consumers happy by ensuring the 
continuity of electricity delivery under normal and abnormal conditions. On occurrence of a 
permanent fault, the electric supply to all download feeder sections is interrupted with power outage 
of all loads until the maintenance crew move to fix the faulty section. This reflects itself on a 
negative impact on the network reliability indices including network average interruption duration 
and frequency indices. With the increasing demand for electricity, power distribution utilities must 
provide an efficient and appropriate Service Restoration strategy to restore customers as soon as 
possible after power outages. A self-healing is defined as recovering the all out-of-service loads in 
the shortest time possible without violating the network operating-constraints. This paper is aimed 
at proposing a smart technique based on a genetic algorithm and load-curve as well as the feedercurve to recover the out-of-service loads following a permanent fault in the power distribution 
network. The proposed algorithm is tested on IEEE 16-bus system in various scenarios. It was 
found that using this proposed method would lead to optimal, accurate, and applicable solutions for 
service restoration in distribution networks. The proposed technique showed better improvements
when compared with that achieved by other methods reported in the literature.